#' Create ExpressionSet.
#'
#' \code{createES} function produces an ExpressionSet object from given data,
#' and exports it to global scope.
#'
#' @param data Gene expression matrix.
#'
#' @param pData Matrix with phenotypical data.
#'
#' @param varLabels Names of phenoData columns.
#'
#' @param fData Matrix with feature data.
#'
#' @param fvarLabels Names of featureData columns.
#'
#' @param eData List with experimentData
#'
#' @return produced ExpressionSet object
#'
#' @import Biobase
#' @importFrom methods new
#'
#' @examples
#' \dontrun{
#' data <- matrix(1:15, 5, 3)
#' pData <- c("A", "B", "C")
#' varLabels <- "cat"
#' fData <- c("p", "r", "s", "t", "u")
#' fvarLabels <- "id"
#' eData <- list(name="", lab="", contact="", title="", url="", other=list(), pubMedIds="")
#' createES(data, pData, varLabels, fData, fvarLabels, eData)
#' }
#' @keywords internal
createES <- function(data, pData, varLabels, fData, fvarLabels, eData) {
phenoData <- AnnotatedDataFrame(data.frame(pData, stringsAsFactors = FALSE))
varLabels(phenoData) <- varLabels
featureData <- AnnotatedDataFrame(data.frame(fData, stringsAsFactors = FALSE))
varLabels(featureData) <- fvarLabels
ed <- new ("MIAME",
name=eData$name,
lab=eData$lab,
title=eData$title,
contact=eData$contact,
pubMedIds=eData$pubMedIds,
url=eData$url,
other=eData$other)
es <- ExpressionSet(assayData = data,
phenoData = phenoData,
featureData = featureData,
experimentData = ed)
assign("es", es, envir = parent.frame())
es
}
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